Evidence map›Paper›PMID 31625949›Full record

ArticleJournal of medical Internet research2019

A Protocol-Driven, Bedside Digital Conversational Agent to Support Nurse Teams and Mitigate Risks of Hospitalization in Older Adults: Case Control Pre-Post Study.

Nicholas Bott, Sharon Wexler, Lin Drury, Chava Pollak, Victor Wang, Kathleen Scher, Sharon Narducci

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 3 pooled it
7.1field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed, 3 syntheses or guidelines pooled it, 63 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 1 country.

Nicholas BottClinical Excellence Research Center, Department of Medicine, Stanford University School of Medicine, Stanford, CA, United States.ORCID 0000-0001-5709-4261
Sharon WexlerPace University, New York, NY, United States.ORCID 0000-0003-0064-348X
Lin DruryPace University, New York, NY, United States.ORCID 0000-0002-2196-6707
Chava PollakPace University, New York, NY, United States.ORCID 0000-0002-5102-5940
Victor WangCare.Coach, Millbrae, CA, United States.ORCID 0000-0001-7493-1981
Kathleen ScherJamaica Hospital Medical Center, New York, NY, United States.ORCID 0000-0003-4228-1958
Sharon NarducciJamaica Hospital Medical Center, New York, NY, United States.ORCID 0000-0001-9154-8394
Pace University · USJamaica Hospital · USStanford University · US

Funding

A Protocol-Driven, Digital Conversational Agent at the Hospital Bedside to Support Nurse Teams and to Mitigate Delirium and Falls RiskR44NR017842 · NINR · CARE.COACH CORPORATION · PI WANG, VICTOR · 2018 to 2020
$1.3M
NINR NIH HHS R44 NR017842
6 · The paper itself

Abstract

backgroundHospitalized older adults often experience isolation and disorientation while receiving care, placing them at risk for many inpatient complications, including loneliness, depression, delirium, and falls. Embodied conversational agents (ECAs) are technological entities that can interact with people through spoken conversation. Some ECAs are also relational agents, which build and maintain socioemotional relationships with people across multiple interactions. This study utilized a novel form of relational ECA, provided by Care Coach (care.coach, inc): an animated animal avatar on a tablet device, monitored and controlled by live health advocates. The ECA implemented algorithm-based clinical protocols for hospitalized older adults, such as reorienting patients to mitigate delirium risk, eliciting toileting needs to prevent falls, and engaging patients in social interaction to facilitate social engagement. Previous pilot studies of the Care Coach avatar have demonstrated the ECA's usability and efficacy in home-dwelling older adults. Further study among hospitalized older adults in a larger experimental trial is needed to demonstrate its effectiveness.

objectiveThe aim of the study was to examine the effect of a human-in-the-loop, protocol-driven relational ECA on loneliness, depression, delirium, and falls among diverse hospitalized older adults.

methodsThis was a clinical trial of 95 adults over the age of 65 years, hospitalized at an inner-city community hospital. Intervention participants received an avatar for the duration of their hospital stay; participants on a control unit received a daily 15-min visit from a nursing student. Measures of loneliness (3-item University of California, Los Angeles Loneliness Scale), depression (15-item Geriatric Depression Scale), and delirium (confusion assessment method) were administered upon study enrollment and before discharge.

resultsParticipants who received the avatar during hospitalization had lower frequency of delirium at discharge (P<.001), reported fewer symptoms of loneliness (P=.01), and experienced fewer falls than control participants. There were no significant differences in self-reported depressive symptoms.

conclusionsThe study findings validate the use of human-in-the-loop, relational ECAs among diverse hospitalized older adults.

Indexed as

AgedAged, 80 and overCase-Control StudiesCommunicationFemaleHospitalizationHumansInterpersonal RelationsMaleNursesPilot ProjectsTelemedicinechatbotdeliriumdigital healthembodied conversational agentfallsinformation and communication technologylonelinessolder adultsrelational agent

Identifiers

PMID31625949
PMCPMC6913375
OpenAlexW2969720013

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.